In signal processing, the Nyquist rate, named after Harry Nyquist, is a value (in units of samples per second or hertz, Hz) equal to twice the highest frequency (bandwidth) of a given function or signal. When the function is digitized at a higher sample rate (see ), the resulting discrete-time sequence is said to be free of the distortion known as aliasing. Conversely, for a given sample-rate the corresponding Nyquist frequency in Hz is one-half the sample-rate. Note that the Nyquist rate is a property of a continuous-time signal, whereas Nyquist frequency is a property of a discrete-time system. The term Nyquist rate is also used in a different context with units of symbols per second, which is actually the field in which Harry Nyquist was working. In that context it is an upper bound for the symbol rate across a bandwidth-limited baseband channel such as a telegraph line or passband channel such as a limited radio frequency band or a frequency division multiplex channel. When a continuous function, is sampled at a constant rate, samples/second, there is always an unlimited number of other continuous functions that fit the same set of samples. But only one of them is bandlimited to cycles/second (hertz), which means that its Fourier transform, is for all The mathematical algorithms that are typically used to recreate a continuous function from samples create arbitrarily good approximations to this theoretical, but infinitely long, function. It follows that if the original function, is bandlimited to which is called the Nyquist criterion, then it is the one unique function the interpolation algorithms are approximating. In terms of a function's own bandwidth as depicted here, the Nyquist criterion is often stated as And is called the Nyquist rate for functions with bandwidth When the Nyquist criterion is not met say, a condition called aliasing occurs, which results in some inevitable differences between and a reconstructed function that has less bandwidth. In most cases, the differences are viewed as distortion.